IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v209y2018icp489-501.html
   My bibliography  Save this article

An integrated systemic method for supply reliability assessment of natural gas pipeline networks

Author

Listed:
  • Su, Huai
  • Zhang, Jinjun
  • Zio, Enrico
  • Yang, Nan
  • Li, Xueyi
  • Zhang, Zongjie

Abstract

A systematic method is developed for supply reliability assessment of natural gas pipeline networks. In the developed method, the integration of stochastic processes, graph theory and thermal-hydraulic simulation is performed accounting for uncertainty and complexity. The supply capacity of a pipeline network depends on the unit states and the network structure, both of which change stochastically because of stochastic failures of the units. To describe this, in this work a capacity network stochastic model is developed, based on Markov modeling and graph theory. The model is embedded in an optimization algorithm to compute the capacities of the pipeline network under different scenarios and analyze the consequences of failures of units in the system. Indices of supply reliability and risk are developed with respect to two aspects: global system and individual customers. In the case study, a gas pipeline network is considered and the results are analyzed in detail.

Suggested Citation

  • Su, Huai & Zhang, Jinjun & Zio, Enrico & Yang, Nan & Li, Xueyi & Zhang, Zongjie, 2018. "An integrated systemic method for supply reliability assessment of natural gas pipeline networks," Applied Energy, Elsevier, vol. 209(C), pages 489-501.
    • Handle: RePEc:eee:appene:v:209:y:2018:i:c:p:489-501
    DOI: 10.1016/j.apenergy.2017.10.108
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261917315568
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2017.10.108?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Du, Y.F. & Jiang, L. & Li, Y.Z. & Counsell, J. & Smith, J.S., 2016. "Multi-objective demand side scheduling considering the operational safety of appliances," Applied Energy, Elsevier, vol. 179(C), pages 864-874.
    2. Villada, Juan & Olaya, Yris, 2013. "A simulation approach for analysis of short-term security of natural gas supply in Colombia," Energy Policy, Elsevier, vol. 53(C), pages 11-26.
    3. Wang, Zhuoyang & Chen, Guo & Hill, David J. & Dong, Zhao Yang, 2016. "A power flow based model for the analysis of vulnerability in power networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 460(C), pages 105-115.
    4. Shin, Joohyun & Lee, Jay H. & Realff, Matthew J., 2017. "Operational planning and optimal sizing of microgrid considering multi-scale wind uncertainty," Applied Energy, Elsevier, vol. 195(C), pages 616-633.
    5. Hao, Xiaoqing & An, Haizhong & Qi, Hai & Gao, Xiangyun, 2016. "Evolution of the exergy flow network embodied in the global fossil energy trade: Based on complex network," Applied Energy, Elsevier, vol. 162(C), pages 1515-1522.
    6. Praks, Pavel & Kopustinskas, Vytis & Masera, Marcelo, 2015. "Probabilistic modelling of security of supply in gas networks and evaluation of new infrastructure," Reliability Engineering and System Safety, Elsevier, vol. 144(C), pages 254-264.
    7. Nicholson, Charles D. & Barker, Kash & Ramirez-Marquez, Jose E., 2016. "Flow-based vulnerability measures for network component importance: Experimentation with preparedness planning," Reliability Engineering and System Safety, Elsevier, vol. 145(C), pages 62-73.
    8. Enrico Zio, 2013. "The Monte Carlo Simulation Method for System Reliability and Risk Analysis," Springer Series in Reliability Engineering, Springer, edition 127, number 978-1-4471-4588-2, September.
    9. Sameer Al-Dahidi & Francesco Di Maio & Piero Baraldi & Enrico Zio, 2017. "A locally adaptive ensemble approach for data-driven prognostics of heterogeneous fleets," Post-Print hal-01652222, HAL.
    10. Verdejo, Humberto & Awerkin, Almendra & Saavedra, Eugenio & Kliemann, Wolfgang & Vargas, Luis, 2016. "Stochastic modeling to represent wind power generation and demand in electric power system based on real data," Applied Energy, Elsevier, vol. 173(C), pages 283-295.
    11. Enrico Zio, 2013. "System Reliability and Risk Analysis by Monte Carlo Simulation," Springer Series in Reliability Engineering, in: The Monte Carlo Simulation Method for System Reliability and Risk Analysis, edition 127, chapter 0, pages 59-81, Springer.
    12. Chertkov, Michael & Backhaus, Scott & Lebedev, Vladimir, 2015. "Cascading of fluctuations in interdependent energy infrastructures: Gas-grid coupling," Applied Energy, Elsevier, vol. 160(C), pages 541-551.
    13. Cardoso, Sónia R. & Paula Barbosa-Póvoa, Ana & Relvas, Susana & Novais, Augusto Q., 2015. "Resilience metrics in the assessment of complex supply-chains performance operating under demand uncertainty," Omega, Elsevier, vol. 56(C), pages 53-73.
    14. Khakzad, Nima & Reniers, Genserik, 2015. "Using graph theory to analyze the vulnerability of process plants in the context of cascading effects," Reliability Engineering and System Safety, Elsevier, vol. 143(C), pages 63-73.
    15. Fu, Xueqian & Sun, Hongbin & Guo, Qinglai & Pan, Zhaoguang & Zhang, Xiurong & Zeng, Shunqi, 2017. "Probabilistic power flow analysis considering the dependence between power and heat," Applied Energy, Elsevier, vol. 191(C), pages 582-592.
    16. Shan, Xiaofang & Wang, Peng & Lu, Weizhen, 2017. "The reliability and availability evaluation of repairable district heating networks under changeable external conditions," Applied Energy, Elsevier, vol. 203(C), pages 686-695.
    17. Li, Gengfeng & Bie, Zhaohong & Kou, Yu & Jiang, Jiangfeng & Bettinelli, Mattia, 2016. "Reliability evaluation of integrated energy systems based on smart agent communication," Applied Energy, Elsevier, vol. 167(C), pages 397-406.
    18. Awudu, Iddrisu & Zhang, Jun, 2013. "Stochastic production planning for a biofuel supply chain under demand and price uncertainties," Applied Energy, Elsevier, vol. 103(C), pages 189-196.
    19. Cadini, Francesco & Agliardi, Gian Luca & Zio, Enrico, 2017. "A modeling and simulation framework for the reliability/availability assessment of a power transmission grid subject to cascading failures under extreme weather conditions," Applied Energy, Elsevier, vol. 185(P1), pages 267-279.
    20. Zio, Enrico, 2016. "Challenges in the vulnerability and risk analysis of critical infrastructures," Reliability Engineering and System Safety, Elsevier, vol. 152(C), pages 137-150.
    21. Wang, Xiaonan & Palazoglu, Ahmet & El-Farra, Nael H., 2015. "Operational optimization and demand response of hybrid renewable energy systems," Applied Energy, Elsevier, vol. 143(C), pages 324-335.
    22. Rimkevicius, Sigitas & Kaliatka, Algirdas & Valincius, Mindaugas & Dundulis, Gintautas & Janulionis, Remigijus & Grybenas, Albertas & Zutautaite, Inga, 2012. "Development of approach for reliability assessment of pipeline network systems," Applied Energy, Elsevier, vol. 94(C), pages 22-33.
    23. Sameer Al-Dahidi & Francesco Di Maio & Piero Baraldi & Enrico Zio, 2017. "A locally adaptive ensemble approach for data-driven prognostics of heterogeneous fleets," Journal of Risk and Reliability, , vol. 231(4), pages 350-363, August.
    24. Johansson, Jonas & Hassel, Henrik & Zio, Enrico, 2013. "Reliability and vulnerability analyses of critical infrastructures: Comparing two approaches in the context of power systems," Reliability Engineering and System Safety, Elsevier, vol. 120(C), pages 27-38.
    25. Kabir, M.N. & Mishra, Y. & Bansal, R.C., 2016. "Probabilistic load flow for distribution systems with uncertain PV generation," Applied Energy, Elsevier, vol. 163(C), pages 343-351.
    26. Yu, Mengmeng & Hong, Seung Ho, 2016. "Supply–demand balancing for power management in smart grid: A Stackelberg game approach," Applied Energy, Elsevier, vol. 164(C), pages 702-710.
    27. Dai, Jun & Das, Diganta & Ohadi, Michael & Pecht, Michael, 2013. "Reliability risk mitigation of free air cooling through prognostics and health management," Applied Energy, Elsevier, vol. 111(C), pages 104-112.
    28. Flouri, Maria & Karakosta, Charikleia & Kladouchou, Charikleia & Psarras, John, 2015. "How does a natural gas supply interruption affect the EU gas security? A Monte Carlo simulation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 44(C), pages 785-796.
    29. Monforti, F. & Szikszai, A., 2010. "A MonteCarlo approach for assessing the adequacy of the European gas transmission system under supply crisis conditions," Energy Policy, Elsevier, vol. 38(5), pages 2486-2498, May.
    30. Ferrario, E. & Pedroni, N. & Zio, E., 2016. "Evaluation of the robustness of critical infrastructures by Hierarchical Graph representation, clustering and Monte Carlo simulation," Reliability Engineering and System Safety, Elsevier, vol. 155(C), pages 78-96.
    31. Hu, Ming-Che & Lu, Su-Ying & Chen, Yen-Haw, 2016. "Stochastic–multiobjective market equilibrium analysis of a demand response program in energy market under uncertainty," Applied Energy, Elsevier, vol. 182(C), pages 500-506.
    32. Enrico Zio, 2013. "Monte Carlo Simulation: The Method," Springer Series in Reliability Engineering, in: The Monte Carlo Simulation Method for System Reliability and Risk Analysis, edition 127, chapter 0, pages 19-58, Springer.
    33. Xie, Shanshan & He, Hongwen & Peng, Jiankun, 2017. "An energy management strategy based on stochastic model predictive control for plug-in hybrid electric buses," Applied Energy, Elsevier, vol. 196(C), pages 279-288.
    34. Johansson, Jonas & Hassel, Henrik, 2010. "An approach for modelling interdependent infrastructures in the context of vulnerability analysis," Reliability Engineering and System Safety, Elsevier, vol. 95(12), pages 1335-1344.
    35. Garshasbi, Samira & Kurnitski, Jarek & Mohammadi, Yousef, 2016. "A hybrid Genetic Algorithm and Monte Carlo simulation approach to predict hourly energy consumption and generation by a cluster of Net Zero Energy Buildings," Applied Energy, Elsevier, vol. 179(C), pages 626-637.
    36. Lo Prete, Chiara & Hobbs, Benjamin F., 2016. "A cooperative game theoretic analysis of incentives for microgrids in regulated electricity markets," Applied Energy, Elsevier, vol. 169(C), pages 524-541.
    37. Ouyang, Min, 2014. "Review on modeling and simulation of interdependent critical infrastructure systems," Reliability Engineering and System Safety, Elsevier, vol. 121(C), pages 43-60.
    38. Bassamzadeh, Nastaran & Ghanem, Roger, 2017. "Multiscale stochastic prediction of electricity demand in smart grids using Bayesian networks," Applied Energy, Elsevier, vol. 193(C), pages 369-380.
    39. Austvik, Ole Gunnar, 2016. "The Energy Union and security-of-gas supply," Energy Policy, Elsevier, vol. 96(C), pages 372-382.
    40. Enrico Zio, 2013. "System Reliability and Risk Analysis," Springer Series in Reliability Engineering, in: The Monte Carlo Simulation Method for System Reliability and Risk Analysis, edition 127, chapter 0, pages 7-17, Springer.
    41. Fichera, Alberto & Frasca, Mattia & Volpe, Rosaria, 2017. "Complex networks for the integration of distributed energy systems in urban areas," Applied Energy, Elsevier, vol. 193(C), pages 336-345.
    42. Mo, Hua-Dong & Li, Yan-Fu & Zio, Enrico, 2016. "A system-of-systems framework for the reliability analysis of distributed generation systems accounting for the impact of degraded communication networks," Applied Energy, Elsevier, vol. 183(C), pages 805-822.
    43. Szikszai, A. & Monforti, F., 2011. "GEMFLOW: A time dependent model to assess responses to natural gas supply crises," Energy Policy, Elsevier, vol. 39(9), pages 5129-5136, September.
    44. Nanduri, Vishnu & Saavedra-Antolínez, Ivan, 2013. "A competitive Markov decision process model for the energy–water–climate change nexus," Applied Energy, Elsevier, vol. 111(C), pages 186-198.
    45. Du, Ruijin & Wang, Ya & Dong, Gaogao & Tian, Lixin & Liu, Yixiao & Wang, Minggang & Fang, Guochang, 2017. "A complex network perspective on interrelations and evolution features of international oil trade, 2002–2013," Applied Energy, Elsevier, vol. 196(C), pages 142-151.
    46. Kikuchi, Yasunori & Kimura, Seiichiro & Okamoto, Yoshitaka & Koyama, Michihisa, 2014. "A scenario analysis of future energy systems based on an energy flow model represented as functionals of technology options," Applied Energy, Elsevier, vol. 132(C), pages 586-601.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Su, Huai & Zio, Enrico & Zhang, Jinjun & Li, Xueyi, 2018. "A systematic framework of vulnerability analysis of a natural gas pipeline network," Reliability Engineering and System Safety, Elsevier, vol. 175(C), pages 79-91.
    2. Zhu, Jianhua & Peng, Yan & Gong, Zhuping & Sun, Yanming & Lai, Chaoan & Wang, Qing & Zhu, Xiaojun & Gan, Zhongxue, 2019. "Dynamic analysis of SNG and PNG supply: The stability and robustness view #," Energy, Elsevier, vol. 185(C), pages 717-729.
    3. Yu, Weichao & Wen, Kai & Min, Yuan & He, Lei & Huang, Weihe & Gong, Jing, 2018. "A methodology to quantify the gas supply capacity of natural gas transmission pipeline system using reliability theory," Reliability Engineering and System Safety, Elsevier, vol. 175(C), pages 128-141.
    4. Chen, Qian & Zuo, Lili & Wu, Changchun & Cao, Yankai & Bu, Yaran & Chen, Feng & Sadiq, Rehan, 2021. "Supply reliability assessment of a gas pipeline network under stochastic demands," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    5. Abedi, Amin & Gaudard, Ludovic & Romerio, Franco, 2019. "Review of major approaches to analyze vulnerability in power system," Reliability Engineering and System Safety, Elsevier, vol. 183(C), pages 153-172.
    6. Yu, Weichao & Song, Shangfei & Li, Yichen & Min, Yuan & Huang, Weihe & Wen, Kai & Gong, Jing, 2018. "Gas supply reliability assessment of natural gas transmission pipeline systems," Energy, Elsevier, vol. 162(C), pages 853-870.
    7. Zhou, Xingyuan & van Gelder, P.H.A.J.M. & Liang, Yongtu & Zhang, Haoran, 2020. "An integrated methodology for the supply reliability analysis of multi-product pipeline systems under pumps failure," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    8. Xuejie Li & Yuan Xue & Yuxing Li & Qingshan Feng, 2022. "An Optimization Method for a Compressor Standby Scheme Based on Reliability Analysis," Energies, MDPI, vol. 15(21), pages 1-16, November.
    9. Wang, WuChang & Zhang, Yi & Li, YuXing & Hu, Qihui & Liu, Chengsong & Liu, Cuiwei, 2022. "Vulnerability analysis method based on risk assessment for gas transmission capabilities of natural gas pipeline networks," Reliability Engineering and System Safety, Elsevier, vol. 218(PB).
    10. Cabrales, Sergio & Valencia, Carlos & Ramírez, Carlos & Ramírez, Andrés & Herrera, Juan & Cadena, Angela, 2022. "Stochastic cost-benefit analysis to assess new infrastructure to improve the reliability of the natural gas supply," Energy, Elsevier, vol. 246(C).
    11. Chao Fang & Piao Dong & Yi-Ping Fang & Enrico Zio, 2020. "Vulnerability analysis of critical infrastructure under disruptions: An application to China Railway High-speed," Journal of Risk and Reliability, , vol. 234(2), pages 235-245, April.
    12. Fu, Xueqian & Zhang, Xiurong & Qiao, Zheng & Li, Gengyin, 2019. "Estimating the failure probability in an integrated energy system considering correlations among failure patterns," Energy, Elsevier, vol. 178(C), pages 656-666.
    13. Yu, Weichao & Gong, Jing & Song, Shangfei & Huang, Weihe & Li, Yichen & Zhang, Jie & Hong, Bingyuan & Zhang, Ye & Wen, Kai & Duan, Xu, 2019. "Gas supply reliability analysis of a natural gas pipeline system considering the effects of underground gas storages," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    14. Yao Wang & Xinqin Gao & Yuanfeng Cai & Mingshun Yang & Shujuan Li & Yan Li, 2020. "Reliability Evaluation for Aviation Electric Power System in Consideration of Uncertainty," Energies, MDPI, vol. 13(5), pages 1-22, March.
    15. Chen, Qian & Zuo, Lili & Wu, Changchun & Bu, Yaran & Lu, Yifei & Huang, Yanfei & Chen, Feng, 2020. "Short-term supply reliability assessment of a gas pipeline system under demand variations," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    16. Corrado lo Storto, 2019. "An SNA-DEA Prioritization Framework to Identify Critical Nodes of Gas Networks: The Case of the US Interstate Gas Infrastructure," Energies, MDPI, vol. 12(23), pages 1-18, December.
    17. Galvan, Giulio & Agarwal, Jitendra, 2020. "Assessing the vulnerability of infrastructure networks based on distribution measures," Reliability Engineering and System Safety, Elsevier, vol. 196(C).
    18. Guowang Meng & Hongle Li & Bo Wu & Guangyang Liu & Huazheng Ye & Yiming Zuo, 2023. "Prediction of the Tunnel Collapse Probability Using SVR-Based Monte Carlo Simulation: A Case Study," Sustainability, MDPI, vol. 15(9), pages 1-21, April.
    19. Michael Saidani & Alissa Kendall & Bernard Yannou & Yann Leroy & François Cluzel, 2019. "Closing the loop on platinum from catalytic converters: Contributions from material flow analysis and circularity indicators," Post-Print hal-02094798, HAL.
    20. Zhaoming Yang & Qi Xiang & Yuxuan He & Shiliang Peng & Michael Havbro Faber & Enrico Zio & Lili Zuo & Huai Su & Jinjun Zhang, 2023. "Resilience of Natural Gas Pipeline System: A Review and Outlook," Energies, MDPI, vol. 16(17), pages 1-19, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:209:y:2018:i:c:p:489-501. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.